A rod \(AB\) of length 0.81 m and mass 5 kg is in equilibrium with the end \(A\) on a rough floor and the end \(B\) against a very rough vertical wall. The rod is in a vertical plane perpendicular to the wall and is inclined at \(45^{\circ}\) to the horizontal. The centre of gravity of the rod is at \(G\), where \(AG = 0.21\) m. The coefficient of friction between the rod and the floor is 0.2, and the coefficient of friction between the rod and the wall is 1.0. Show that the friction cannot be limiting at both \(A\) and \(B\). A mass of 5 kg is attached to the rod at the point \(P\) such that now the friction is limiting at both \(A\) and \(B\). Determine the length of \(AP\).
I have \(k\) different keys on my key ring. When I come home at night I try one key after another until I find the key that fits my front door. What is the probability that I find the correct key in exactly \(n\) attempts in each of the following three cases?
Every person carries two genes which can each be either of type \(A\) or of type \(B\). It is known that \(81\%\) of the population are \(AA\) (i.e. both genes are of type \(A\)), \(18\%\) are \(AB\) (i.e. there is one gene of type \(A\) and one of type \(B\)) and \(1\%\) are \(BB\). A child inherits one gene from each of its parents. If one parent is \(AA\), the child inherits a gene of type \(A\) from that parent; if the parent is \(BB\), the child inherits a gene of type \(B\) from that parent; if the parent is \(AB\), the inherited gene is equally likely to be \(A\) or \(B\).
The random variable \(X\) is uniformly distributed on the interval \([-1,1]\). Find \(\E(X^2)\) and \(\var (X^2)\). A second random variable \(Y\), independent of \(X\), is also uniformly distributed on \([-1,1]\), and \(Z=Y-X\). Find \(\E(Z^2)\) and show that \(\var (Z^2) = 7 \var (X^2)\).
Solution: \(X \sim U(-1,1)\) \begin{align*} \E[X^2] &= \int_{-1}^1 \frac12 x^2 \, dx \\ &= \frac{1}{6} \left [ x^3 \right]_{-1}^1 \\ &= \frac{1}{3} \end{align*} \begin{align*} \E[X^4] &= \int_{-1}^1 \frac12 x^4 \, dx \\ &= \frac{1}{10} \left [ x^5 \right]_{-1}^1 \\ &= \frac{1}{5} \end{align*} \begin{align*} \var[X^2] &=\E[X^4] - \E[X^2]^2 \\ &= \frac{1}{5} - \frac{1}{9} \\ &= \frac{4}{45} \end{align*} \begin{align*} \E(Z^2) &= \E(Y^2 - 2XY+Z^2) \\ &= \E(Y^2) - 2\E(X)\E(Y)+\E(Z^2) \\ &= \frac{1}{3} - 0 + \frac{1}{3} \\ &= \frac{2}{3} \end{align*} \begin{align*} \E[Z^4] &= \E[Y^4 -4Y^3X+6Y^2X^2-4YX^3+X^4] \\ &= \E[Y^4]-4\E[Y^3]\E[X]+6\E[Y^2]\E[X^2]-4\E[Y]\E[X^3]+\E[X^4] \\ &= \frac{1}{5}+6 \frac{1}{3} \frac13 + \frac{1}{5} \\ &= \frac{2}{5} + \frac{2}{3} \\ &= \frac{16}{15} \end{align*} \begin{align*} \var(Z^2) &= \E(Z^4) - \E(Z^2) \\ &= \frac{16}{15} - \frac{4}{9} \\ &= \frac{28}{45} \\ &= 7 \var(X^2) \end{align*}